The present invention relates to a noise detection apparatus and a noise detection method for detecting the level of random noises mixed into video signals displayed on a video display apparatus, such as a TV and a monitor screen, and also a noise reduction apparatus and a noise reduction method for reducing such random noises depending on detected noise levels.
Known noise reduction apparatuses employ noise reduction techniques such as coring and recursive filtering.
FIG. 1 shows a block diagram of a known noise reduction apparatus employing coring for noise reduction.
In FIG. 1, a video signal input via an input terminal 200 is supplied to a subtractor 201, a high-pass filter (HPF) 202, and a noise detector 203.
The HPF 202 extracts high-frequency components of the input video signal and supplies them to the subtractor 201 and also a coring unit 204. The subtractor 201 subtracts the high-frequency components from the input video signal to extract low-frequency components of the video signal and supplies them to an adder 205.
The noise detector 203 extracts a high-frequency-component signal of the input video signal during each vertical or horizontal blanking interval to determine that a higher-level high-frequency-component signal carries larger random noises. Detection during the vertical or horizontal blanking interval is accurate due to no images during the interval. A resultant noise detection signal is supplied to the coring unit 204.
The coring unit 204 removes low-level components lower than a predetermined level from the high-frequency components of the video signal supplied by the HPF 202 according to its coring characteristics and supplies the remaining components to the adder 205. Noises are reduced through coring because they are normally low-level high-frequency components.
FIG. 2 shows the coring characteristics with output signal levels on the axis of ordinate versus input signal levels on the axis of abscissa. It is shown that an output signal level is zero when the absolute value of an input signal level is equal to or smaller than the absolute value of a threshold level Th whereas the former depends on the latter when the latter is larger than |Th|; a larger |Th| providing a higher noise reduction performace.
According to the coring characteristics shown in FIG. 2, the coring unit 204 varies the absolute value of the threshold level Th, in response to the resultant noise detection signal supplied from the noise detector 203. In detail, the coring unit 204 increases (decreases) |Th| as the random noises detected by the detector 203 are larger (smaller), thus outputting noise-reduced high-frequency components.
In FIG. 1, the adder 205 adds the noise-reduced high-frequency components and the low-frequency components from the subtractor 201, to output a noise-reduced video signal via an output terminal 206.
As described, in the known noise reduction apparatus shown in FIG. 1, the coring unit 204 outputs a lower-level video signal, with a smaller |Th| in the coring characteristics for smaller random noises. Thus, the known apparatus reduces a phenomenon in which not only noise components but also lower-level video signal components are inevitably removed when an input video signal carries smaller noises.
FIG. 3 shows a block diagram of another known noise reduction apparatus employing recursive filtering for noise reduction.
In FIG. 3, a video signal input via an input terminal 210 is supplied to an adder 211, a subtractor 212, and a noise detector 213.
The output signal of the adder 211 is output via an output terminal 214 as an output video signal and further supplied to a frame delay unit 215. The unit 215 delays the output video signal by one frame and supplies the frame-delayed video signal to the subtractor 212. The subtractor 212 subtracts the input video signal from the frame-delayed video signal to output a resultant subtraction signal carrying no interframe correlation to an attenuator 216. The adder 211 adds the input signal and the output signal of the attenuator 216 to output an output signal via the output terminal 214.
Like the noise detector 203 shown in FIG. 1, the noise detector 213 extracts a high-frequency-component signal of the input video signal during a vertical or a horizontal blanking interval to determine that a higher-level high-frequency-component signal carries larger random noises. Detection during the vertical or horizontal blanking interval is accurate due to no images during the interval. A resultant noise detection signal is supplied to the attenuator 216.
In general, a video signal carrying a still image or an image with almost no motion exhibits a strong interframe correlation whereas random noises mixed in the video signal exhibit no correlation.
Thus, the output signal of the subtractor 212 that is an interframe differential signal carries low-level noise components.
Any attenuation coefficient “k” other than zero at the attenuator 216 causes recursive addition of the noise components (output by the subtractor 212) along the loop from the adder 211 to the attenuator 216 via the frame delay unit 215 and the subtractor 212, with weighting of “k”, thus achieving recursive noise reduction, with a noise-reduced video signal being output via the output terminal 214.
In contrast, for a video signal carrying a moving image, the output signal of the subtractor 212 (an interframe differential signal) carries high-level motion components. In response to the high-level motion components, an attenuation coefficient “k” of zero gives an output of zero to the adder 211 from the attenuator 216. Then, the adder 211 adds zero to the input video signal supplied via the input terminal 210, with no recursive noise reduction. The input video signal thus passes through the adder 211 and is output via the output terminal 214.
FIG. 4 shows exemplary non-linear attenuation characteristics for the attenuator 216, with output signal levels on the axis of ordinate versus input signal levels on the axis of abscissa. An attenuation ratio “k” (k=y/x) is adjusted to be closer to 1 for an input signal that can be treated as noise components when the absolute value of its level is smaller than |Xn|. In contrast, “k” is adjusted to be closer to zero as the absolute value of an input signal level becomes larger. In particular, the ratio “k” is set at zero when the absolute value of an input signal level is equal to or larger than |Xn| because such a signal level can be treated as motion components.
The attenuation characteristics of the attenuator 216 is adjusted to have a larger absolute value |Xn| for larger random noises detected by the noise detector 213 to achieve recursive noise reduction, in response to the resultant noise detection signal from the detector 213.
As described, the known noise reduction apparatus shown in FIG. 3 performs recursive noise reduction with weighting an attenuation coefficient “k” on a video signal carrying a still image or an image with almost no motion, thus achieving reduction of only noise components while high-frequency components remaining unchanged. Because, for such a video signal, an interframe differential signal supplied from the subtractor 212 to the attenuator 216 has a smaller absolute value than |Xn| (FIG. 4).
A further known frame-recursive noise reduction apparatus is disclosed, for example, in Japanese Unexamined Patent Publication No. 2000-134510 (referred to as document 1, hereinafter).
The apparatus disclosed in the document 1 functions as follows: An input video signal is multiplied by “1−K” whereas an output video signal is delayed by one frame and multiplied by “K”. The frame-delayed and “K”-multiplied output signal is added to the “K−1”-multiplied input signal, thus generating a noise-reduced output video signal with no frame correlation. Recursive coefficient adjustment is performed in which the coefficient “K” is adjusted to be larger for higher noise reduction performance to an input video signal carrying still images with no afterimages whereas be smaller to reduce afterimage interference to an input video signal carrying moving images and thus having afterimages.
The known apparatus in the document 1 is equipped with a motion detector to determine that an input video signal carries a still image or a moving image depending on the degree of an interframe difference between a present frame and a previous frame in the video signal in relation to a predetermined threshold level. The coefficient “K” is varied according to whether the input video signal carries a still image or a moving image.
The known apparatus in the document 1 is equipped further with a field strength detector that raises the threshold level for the motion detector in determination of whether an input video signal carries a still image or a moving image when an electric field strength of an input video signal is weaker than a predetermined level, thus adaptively controlling the coefficient “K” depending on the field strength level.
The field strength detector is used when the known apparatus is installed in a TV in which the motion detector could erroneously determine that an input video signal carries a moving image even if it carries a still image due to noises spread over a screen when the video signal is a low-S/N signal.
Although several advantages of the known apparatuses are discussed above, these apparatuses have the following disadvantages:
The known noise reduction apparatus shown in FIG. 1 employs spatial filtering to achieve noise reduction irrespective of motion of images. It is, however, a non-recursive type and hence a relatively larger |Th| in the coring characteristics could inevitably cause that not only noises but also minute high-frequency components are removed, thus improvements in S/N being more or less 3 dB.
Compared to the coring-type apparatus in FIG. 1, the known noise reduction apparatus shown in FIG. 3 employing recursive filtering has much improvement in S/N. Nevertheless, the latter achieves noise reduction only to still images or images with almost no motion. In other words, it will not work for noise reduction in moving images. Moreover, the non-linear attenuation characteristics of the attenuator 216 is required to be changed gradually depending on the noise level detected by the noise detector 213. It is, however, difficult to apply different non-linear attenuation-characteristics modes to the attenuator 216 and gradually change these modes, which could result in a big change in noise reduction performance when the noise level varies.
The known noise reduction apparatus disclosed in the document 1 achieves higher noise reduction performance to still images or images with almost no motion, with adjustments to the coefficient “K” depending on interframe differences, whereas not so effective on moving images due to smaller coefficient “K” for reducing afterimage interference.
When it comes to noise reduction in the vertical and/or horizontal blanking intervals, the noise detectors 203 and 213 shown in FIGS. 1 and 3, respectively, detect the noise level of an input video signal during each blanking interval. In other words, they cannot detect noises for a video signal that has noises on images only (even if they are large) whereas carries no noises during the blanking intervals. Such a signal having noises on images only whereas carrying no noises during the blanking intervals is, for example, an output signal of a video recording/reproduction apparatus in which the output signal carries recorded image only, with blanking intervals being added when the signal is reproduced.
Therefore, the known noise reduction apparatuses shown in FIGS. 1 and 3 cannot achieve high noise reduction performance to such a signal carrying no noises during the blanking interval even if it has large noises on images. The same is true for the known noise reduction apparatus disclosed in the document 1 in which the motion detector is controlled depending on an electric field strength of an input video signal detected through the use of a signal included in the vertical synchronizing period or equalizing period.